Pricing and Packaging: A Strategic Lever for Growth

By David Ronald

Pricing and packaging are often underestimated levers of growth.

While product innovation and marketing tend to gain the spotlight, it’s often the pricing model and how the product is packaged that can ultimately make or break go-to-market success.

Get it right, and you’ll unlock new revenue streams, reduce churn, and boost customer satisfaction. Get it wrong, and even the best product may struggle to gain traction. 

In this blog I explore how you can use pricing and packaging as a strategic lever of growth.

A Synergistic Combination

It’s obvious to everyone that “pricing” refers to how much you charge for your product or service.

But what is “packaging” exactly? Well, “packaging” refers to how you structure your product. For example, what features are included in each plan, how do those features align with customer needs, and what value propositions are communicated at each level.

Together, pricing and packaging define how value is exchanged between you and your customer.

Pricing and packaging decisions must be rooted in customer segmentation. Not all users are the same – some are looking for basic functionality at a low cost, while others demand advanced features, scalability, and dedicated support (and are willing to pay a premium for it).

A one-size-fits-all approach rarely works.

Instead, you should offer tailored tiers or bundles that reflect the needs and willingness to pay of different customer groups.

Why It Matters

Poorly thought-out pricing and packaging can lead to multiple problems.

If the entry-level tier is too generous, users may never upgrade. If premium plans feel overpriced or misaligned with value, customers may churn or choose a competitor.

On the flip side, effective packaging can guide customers naturally toward higher-value plans, increase average revenue per user, and even shape the way the product is used.

For example, many SaaS companies adopt a “freemium to paid” model, where a free tier allows for broad adoption and product-led growth – while paid tiers unlock features for power users or businesses.

Others business chose to offer usage-based pricing to align cost with value (such as charging per API call, seat, or GB stored).  

The key is to make pricing feel fair, transparent, and scalable with customer success.

Optimizing Pricing and Packaging

Here are some bet practices for optimizing pricing and packaging: 

• Research customer value drivers—Conduct interviews, surveys, and willingness-to-pay studies to understand what customers value and how much they’d pay for it.
• Use data to iterate—Pricing and packaging are not set-it-and-forget-it. Use cohort analysis, A/B testing, and revenue metrics to test and refine your approach.
• Communicate clearly—Avoid confusing buyers with pricing pages that create friction. Ensure customers can easily compare plans and understand what they’re getting.
• Anchor with value—Use psychological principles like price anchoring and tier contrast to make higher-tier plans look more attractive.
• Align incentives—Your internal sales and customer success teams should be incentivized to promote the right plans to the right users.

By following these best practices, companies can create pricing and packaging strategies that not only drive revenue but also enhance customer satisfaction and loyalty. 

Conclusion

Pricing and packaging are powerful strategic levers that influence how customers perceive your product, how they engage with it, and ultimately how your business performs.

The most successful companies recognize that pricing and packaging are integral parts of the overall product experience, not just afterthoughts or administrative details.

When thoughtfully designed and continuously refined, pricing and packaging actively create value for you – they will enable you to meet diverse customer needs, encourage adoption and expansion, and foster long-term loyalty.

Mastering pricing and packaging are essential for unlocking sustainable growth and differentiation. So, invest the time and resources to get these elements right, and you’ll set yourself up for success that lasts.

Thanks for reading.

Did you find this blog post helpful. If so, feel free to let me know why by sending an email to david@alphabetworks.com – I look forward to hearing from you.

AI Is Changing the Role of the CMO

By David Ronald 

You're accustomed to navigating change if you are a CMO – rising technologies, evolving customer expectations, emerging channels, and more.

But, today, AI is more than just another trend on the horizon.

It's fundamentally transforming the very fabric of marketing leadership, reshaping how CMOs think, act, and deliver value.

Forrester’s Predictions 2025 report notes that 64% of global B2B marketing leaders plan to increase spending on AI-driven technology in the next year. Forrester analysis also indicates that 30% of US CMOs are directly leading AI efforts in their organization, showing early adoption and internal leadership shifts.

From predictive analytics and content generation to hyper-personalized campaigns and real-time customer insights, AI is no longer an optional add-on – it’s becoming a core competency for today's CMO.  

 

In this blog post I examine what this transformation looks like in practice and what it means for the future of marketing leadership.

(You may also be interested in our blog post 5 Ways Artificial Intelligence Will Improve Marketing ROI.)  

From Intuition to Intelligence—AI as the New Strategic Brain

CMOs have traditionally relied on experience, creativity, and gut instinct to drive strategy.

While those skills are still essential, AI now augments them with speed and scale previously unimaginable.

AI empowers CMOs to: 

• Predict behavior before it happens.
• Deliver personalized experiences at scale.
• Measure impact with precision.
• Identify new opportunities with real-time data.

According to a McKinsey report, organizations that extensively use customer analytics are 23 times more likely to outperform competitors in new customer acquisition and 9x more likely to surpass them in customer loyalty. 

Case Study: Sephora

Sephora uses an AI-powered chatbot and a personalization engine are helping to redefine beauty retail. 

By analyzing customer preferences, previous purchases, and behavior patterns, the brand offers tailored product recommendations, virtual try-ons, and predictive insights.

What were some of the outcomes? 

• A 50% increase in engagement through AI-powered in-app experiences.
• Higher conversion rates from personalized marketing messages.
• Increased customer lifetime value.

These results underscore how AI can create more meaningful, data-driven customer journeys that drive both satisfaction and sales.

Redefining Customer Experience—From Mass Campaigns to Individual Journeys

Many CMOs are shifting from campaign-centric thinking to journey-centric execution.

AI makes this shift possible by enabling real-time, one-to-one marketing, at scale. 

Using machine learning and natural language processing, AI can segment audiences dynamically, test messages continuously, and adjust campaigns instantly.  

This is adaptive learning. 

Case Study: Coca-Cola

Coca-Cola appears to be using AI for everything from analyzing social media conversations to generating creative content.

One notable initiative involved using AI algorithms to create more than 100,000 unique video ads tailored to different audiences across markets.

AI has helped Coca-Cola to accomplish the following: 

• Reduce production costs.
• Increase click-through rates by 4x.
• Boost engagement through hyper-relevant messaging.

This level of personalization would be impossible manually. AI makes it scalable and repeatable. 

The Creative Renaissance—AI as a Co-Creator

AI’s role in marketing creativity is often misunderstood. It enhances human creativity, not replace it.

Some CMOs are learning to embrace AI tools that help generate ideas, optimize content, and even draft copy, freeing teams to focus on higher-order creative thinking.

Tools like ChatGPT, Copy, and Jasper and are already being used for: 

• Blog drafting and content ideation.
• SEO-optimized web copy generation.
• Email subject line testing.
• A/B testing of ad creatives.

As these tools evolve, they are becoming essential collaborators in the creative process, amplifying human ingenuity rather than diminishing it.

Case Study: Heinz and DALL·E

Heinz partnered with OpenAI's DALL·E to explore what "ketchup" looked like in AI-generated imagery. 

The results were consistent – most images resembled the iconic Heinz bottle, reinforcing the brand’s cultural presence.

This campaign delivered these results: 

• Sparked a 10% uplift in brand sentiment.
• Generated significant among of earned media.
• Showcased how AI could be used in a playful, brand-enhancing way.

This is a powerful example of AI as a creative collaborator, not just a data tool. 

Real-Time Insights—The CMO as a Data-Driven Decision Maker

AI has the ability to transform a CMO’s dashboard from retrospective reporting to real-time insight generation.

With AI-powered analytics tools like Adobe Sensei, Google Cloud’s Looker, , and Salesforce Einstein, CMOs can now monitor campaigns, customer behavior, and ROI in real time.

AI can accomplish the following: 

• Identify underperforming channels before money is wasted.
• Detect anomalies in customer churn.
• Recommend budget reallocations based on predictive ROI.
• Model “what-if” scenarios to support strategic decisions.

According to a Salesforce whitepaper, 57% of marketing leaders say AI and machine learning are essential for creating a unified customer view. 

Case Study: Autodesk and IBM Watson

Autodesk used IBM Watson to create “AVA,” an AI-powered customer service agent. 

AVA handled over 30,000 customer support queries per month, reducing response times from days to seconds and freeing up human agents for more complex tasks.  

The ripple effect on marketing was profound: 

• Better insights into customer pain points.
• Improved content strategy.
• Increased Net Promoter Scores (NPS) and retention.

AVA became a source of real-time, structured data - which is “gold” for any CMO. 

Organizational Impact—The CMO as a Change Agent

AI isn’t just changing what CMOs do—it’s changing who they need to be.  

To lead in the AI era, CMOs must: 

• Embrace cross-functional leadership, working closely with data science, IT, and product.
• Build teams with hybrid talent—marketers who understand data and technologists who grasp customer empathy.
• Rethink traditional agency partnerships in favor of AI-powered platforms and in-house capabilities.
• Champion ethical AI use and data privacy.

Here are some of the key skills that CMOs now need: 

Traditional CMO	Modern CMO
Brand building	Data fluency
Channel management	Tech stack fluency
Campaign execution	Continuous experimentation
Storytelling	Story + Strategy + Signal

In other words, a modern CMO must evolve into a Chief Intelligence Officer, guiding the organization not just with creative vision, but with evidence-based foresight.

Looking into the Future

As AI continues to evolve, we can expect to see the following: 

• Generative AI driving even more creative assets, from video scripts to product designs.
• Predictive personalization based on emotion, intent, and context.
• Zero-click marketing where smart assistants (think Alexa, ChatGPT) become the buyer’s interface.
• Autonomous campaign optimization, where AI adjusts spend and content in real-time across channels.
• Voice and conversational AI as dominant marketing channels.

According to a study by Deloitte, companies using AI-powered personalization see a 40% increase in marketing ROI, and that gap will widen as early adopters double down. 

Conclusion

AI is no longer an emerging trend, but the new foundation of modern marketing leadership.  

This requires a full-scale mindset shift for CMOs. The role is evolving from storyteller and brand builder to orchestrator of intelligence, creativity, and real-time strategy.

As the technology accelerates, so too must the marketer’s ability to blend human intuition with machine-driven insight.

The CMOs who thrive in this new era will be those who embrace AI not as a threat, but as a partner, leveraging it to deepen customer relationships, drive smarter decisions, and fuel continuous innovation.

The future belongs to those ready to lead with data, scale with automation, and create with intelligence.

Thanks for reading.

Would you like to discuss this blog post? If so, my email is david@alphabetworks.com – I look forward to hearing from you.